Cable surface damage detection in cable-stayed bridges using optical techniques and image mosaicking. (February 2019)

• Record Type: Journal Article
• Authors: Li, Xinke; Gao, Chao; Guo, Yongcai; He, Fuliang; Shao, Yanhua
• Is Part Of: Optics & laser technology. Volume 110(2019)
• Page Start: 36
• Page End: 43
• Publication Date: 2019-02
• Subjects: Cable-stayed bridge -- Surface damage detection -- Vision inspection system -- Simplified SIFT -- Image mosaicking; Optics -- Periodicals; Lasers -- Periodicals; Electronic journals; 621.366
• DOI: 10.1016/j.optlastec.2018.07.012
• Languages: English
• ISSNs: 0030-3992

Abstract

Highlights: A 4-CCDs vision system is developed and employed to detect cable damage. A faster and simplified SIFT algorithm is proposed for the defect images stitching. RANSAC screening method is carried out for deleting mismatching feature points. The cable damage can be detected and stands out clearly in the mosaic image. Abstract: A vision inspection system is developed for detecting surface damages on cables in long-span cable-stayed bridges. The system consists of a climbing robot, an image processing platform, and 4 fixed cameras. While the climbing robot loads the whole system and ascends along the cables, 4 cameras can continuously acquire cable surface images. Then, image processing techniques can be employed to achieve defect identification. In our optical system, a single image may only collect a part of the whole defect because of the field of view (FOV) of each camera. In order to obtain the morphology of the whole defect, we present an efficient scale-invariant feature transform (SIFT) algorithm to achieve the multi-image mosaic with partially overlapped regions in different defect images. Experimental results demonstrate that the proposed vision inspection technologies are suitable for application to the bridge cables for defect detection and condition assessment.